import plotly.offline as pyo
from plotly.graph_objs import *
import chart_studio.plotly as py
import pandas as pd
from pandas import DataFrame
pyo.offline.init_notebook_mode()
housePrices = pd.read_csv(r"../Data/RegionalHousePricesAndRanksJan16.csv")
regions = ['South West','South East','London',
'East of England','West Midlands','East Midlands',
'Yorkshire and The Humber','North West','North East']
for r in regions:
housePrices[r + "_text"] = "<b>" + r +"</b><br>Average Price: " + housePrices[r + "_avg"].apply(lambda x:
"£{:,}".format(int(round(x, 0)))) + "<br><i>Rank of average price: " + housePrices[r + "_rank"].apply(lambda x:
str(int(x))) + "</i>"
housePrices.head(1)
| Date | South West_avg | South East_avg | London_avg | East of England_avg | West Midlands_avg | East Midlands_avg | Yorkshire and The Humber_avg | North West_avg | North East_avg | ... | North East_rank | South West_text | South East_text | London_text | East of England_text | West Midlands_text | East Midlands_text | Yorkshire and The Humber_text | North West_text | North East_text | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1995-01-01 | 54705.1579 | 64018.87894 | 74435.76052 | 56701.5961 | 45090.91026 | 45544.52227 | 44803.42878 | 43958.48001 | 42076.35411 | ... | 9.0 | <b>South West</b><br>Average Price: £54,705<br... | <b>South East</b><br>Average Price: £64,019<br... | <b>London</b><br>Average Price: £74,436<br><i>... | <b>East of England</b><br>Average Price: £56,7... | <b>West Midlands</b><br>Average Price: £45,091... | <b>East Midlands</b><br>Average Price: £45,545... | <b>Yorkshire and The Humber</b><br>Average Pri... | <b>North West</b><br>Average Price: £43,958<br... | <b>North East</b><br>Average Price: £42,076<br... |
1 rows × 28 columns
traces = []
for r in regions:
traces.append({'type' : 'scatter',
'x' : housePrices['Date'],
'y' : housePrices[r + "_avg"],
'name' : r,
'mode' : 'lines'})
data = Data(traces)
layout = {'title' : "Yearly Changes in Average House Price for English Regions, 1995-2016",
'xaxis' : {'title' : 'Year'},
'yaxis' : {'tickformat' : ",",
'tickprefix' : "£",
'title' : 'Average Price'}}
fig = Figure(data=data, layout=layout)
pyo.iplot(fig)
traces = []
for r in regions:
traces.append({'type' : 'scatter',
'x' : housePrices['Date'],
'y' : housePrices[r + "_avg"],
'name' : r,
'mode' : 'lines',
'text' : housePrices[r + "_text"]})
data = Data(traces)
layout = {'title' : "Yearly Changes in Average House Price for English Regions, 1995-2016",
'xaxis' : {'title' : 'Year'},
'yaxis' : {'tickformat' : ",",
'tickprefix' : "£",
'title' : 'Average Price'}}
fig = Figure(data=data, layout=layout)
pyo.iplot(fig)
traces = []
for r in regions:
traces.append({'type' : 'scatter',
'x' : housePrices['Date'],
'y' : housePrices[r + "_avg"],
'name' : r,
'mode' : 'lines',
'text' : housePrices[r + "_text"],
'hoverinfo' : 'text+x'})
data = Data(traces)
layout = {'title' : "Yearly Changes in Average House Price for English Regions, 1995-2016",
'xaxis' : {'title' : 'Year'},
'yaxis' : {'tickformat' : ",",
'tickprefix' : "£",
'title' : 'Average Price'}}
fig = Figure(data=data, layout=layout)
pyo.iplot(fig)
traces = []
for r in regions:
traces.append({'type' : 'scatter',
'x' : housePrices['Date'],
'y' : housePrices[r + "_avg"],
'name' : r,
'mode' : 'lines',
'text' : housePrices[r + "_text"],
'hoverinfo' : 'text+x'})
data = Data(traces)
layout = {'title' : "Yearly Changes in Average House Price for English Regions, 1995-2016",
'xaxis' : {'title' : 'Year'},
'yaxis' : {'tickformat' : ",",
'tickprefix' : "£",
'title' : 'Average Price'},
'hovermode' : 'closest'}
fig = Figure(data=data, layout=layout)
pyo.iplot(fig)